Abstract
Visual quality control is a demanding task of increasing importance in industrial manufacturing. Both speed and flexibility are of paramount importance for viable and competitive inspection systems. We have developed a dedicated neural network architecture for anomaly detection that can easily be trained by a single presentation of examples and is amenable to massively parallel VLSI implementation. We focus here on our ASIC and prototype system design effort for this network. >
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